Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.01843 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915838310744064 |
|---|---|
| author | Kułakowski, Konrad Szybowski, Jacek |
| author_facet | Kułakowski, Konrad Szybowski, Jacek |
| contents | A project (e.g., writing a collaborative research paper) is often a group effort. At the end, each contributor identifies their contribution, often verbally. The reward, however, is very frequently financial. It leads to the question of what (percentage) share in the creation of the paper is due to individual authors. Different authors may have various opinions on the matter; even worse, their opinions may have different relevance. In this paper, we present simple models that allow aggregation of experts' views, linking the priority of his preference directly to the assessment made by other experts. In this approach, the more significant the contribution of a given expert, the greater the importance of his opinion. The presented method can be considered an attempt to find consensus among peers involved in the same project. Hence, its applications may go beyond the proposed study example of writing a scientific paper. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01843 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | My part is bigger than yours -- assessment within a group of peers Kułakowski, Konrad Szybowski, Jacek Discrete Mathematics Artificial Intelligence A project (e.g., writing a collaborative research paper) is often a group effort. At the end, each contributor identifies their contribution, often verbally. The reward, however, is very frequently financial. It leads to the question of what (percentage) share in the creation of the paper is due to individual authors. Different authors may have various opinions on the matter; even worse, their opinions may have different relevance. In this paper, we present simple models that allow aggregation of experts' views, linking the priority of his preference directly to the assessment made by other experts. In this approach, the more significant the contribution of a given expert, the greater the importance of his opinion. The presented method can be considered an attempt to find consensus among peers involved in the same project. Hence, its applications may go beyond the proposed study example of writing a scientific paper. |
| title | My part is bigger than yours -- assessment within a group of peers |
| topic | Discrete Mathematics Artificial Intelligence |
| url | https://arxiv.org/abs/2407.01843 |